Development and internal validation of a diagnostic prediction model for COVID-19 at time of admission to hospital.

BACKGROUND: Early coronavirus disease 2019 (COVID-19) diagnosis prior to laboratory testing results is crucial for infection control in hospitals. Models exist predicting COVID-19 diagnosis, but significant concerns exist regarding methodology and generalizability. AIM: To generate the first COVID-19 diagnosis risk score for use at the time of hospital admission using the TRIPOD (transparent reporting of a multivariable prediction model for individual prognosis or diagnosis) checklist. DESIGN: A multivariable diagnostic prediction model for COVID-19 using the TRIPOD checklist applied to a large single-centre retrospective observational study of patients with suspected COVID-19. METHODS: 581 individuals were admitted with suspected COVID-19; the majority had laboratory-confirmed COVID-19 (420/581, 72.2%). Retrospective collection was performed of electronic clinical records and pathology data. RESULTS: The final multivariable model demonstrated AUC 0.8535 (95% confidence interval 0.8121-0.8950). The final model used six clinical variables that are routinely available in most low and high-resource settings. Using a cut-off of 2, the derived risk score has a sensitivity of 78.1% and specificity of 86.8%. At COVID-19 prevalence of 10% the model has a negative predictive value (NPV) of 96.5%. CONCLUSIONS: Our risk score is intended for diagnosis of COVID-19 in individuals admitted to hospital with suspected COVID-19. The score is the first developed for COVID-19 diagnosis using the TRIPOD checklist. It may be effective as a tool to rule out COVID-19 and function at different pandemic phases of variable COVID-19 prevalence. The simple score could be used by any healthcare worker to support hospital infection control prior to laboratory testing results.

Improving outcomes in gestational diabetes: does gestational weight gain matter?

AIM: Excessive gestational weight gain increases risk of gestational diabetes mellitus (GDM) but it remains unclear whether weight control after GDM diagnosis improves outcomes. We assessed whether: (1) total gestational weight gain during pregnancy (0-36 weeks); (2) early gestational weight gain (0-28 weeks, before GDM diagnosis); or (3) late gestational weight gain (28-36 weeks, after diagnosis) are associated with maternal-fetal outcomes. METHODS: Some 546 women with GDM who delivered viable singleton infants at a single UK obstetric centre (October 2014 to March 2017) were included in this retrospective observational study. RESULTS: Higher total gestational weight gain was associated with Caesarean section [n = 376; odds ratio (OR) 1.05; confidence intervals (CI) 1.02-1.08, P < 0.001] and large for gestational age (OR 1.08; CI 1.03-1.12, P < 0.001). Higher late gestational weight gain (28-36 weeks; n = 144) was associated with large for gestational age (OR 1.17; CI 1.01-1.37, P < 0.05), instrumental deliveries (OR 1.26; CI 1.03-1.55, P < 0.01), higher total daily insulin doses (36 weeks; beta coefficient 4.37; CI 1.92-6.82, P < 0.001), and higher post-partum 2-h oral glucose tolerance test concentrations (beta coefficient 0.12; CI 0.01-0.22, P < 0.05). Women who avoided substantial weight gain after GDM diagnosis had 0.7 mmol/l lower postnatal 2-h glucose and needed half the amount of insulin/day at 36 weeks compared with women with substantial weight gain after diagnosis. There were no significant associations between early gestational weight gain (0-28 weeks) and pregnancy outcomes. CONCLUSIONS: These findings suggest that controlling gestational weight gain should be a priority following GDM diagnosis to optimize pregnancy outcomes and improve maternal postnatal glucose homeostasis. The period after diagnosis of GDM (often 28 weeks gestation) is not too late to offer lifestyle advice or intervention to improve weight management and pregnancy outcomes.